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Record W2227801330 · doi:10.1136/ebmed-2015-110217

Routine iron supplementation for non-anaemic pregnant women in developed countries needs evaluation

2015· letter· en· W2227801330 on OpenAlexaff
Zulfiqar A Bhutta

Bibliographic record

VenueEvidence-Based Medicine · 2015
Typeletter
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsCentre for Global Health ResearchHospital for Sick Children
Fundersnot available
KeywordsMedicinePregnancyMicronutrientAnemiaPediatricsGastroenterologyFolic acidGynecologyInternal medicineObstetricsPathology

Abstract

fetched live from OpenAlex

Commentary on: Cantor AG, Bougatsos C, Dana T, et al. Routine iron supplementation and screening for iron deficiency anemia in pregnancy: a systematic review for the U.S. Preventive Services Task Force. Ann Intern Med 2015;162:566–76[OpenUrl][1][CrossRef][2][PubMed][3]. The role of appropriate nutrition and micronutrient intake in pregnancy is well established and 19.2% of pregnant women globally are estimated to have iron deficiency anaemia (IDA).1 The corresponding estimates for the Americas and Caribbean are 15.2% (11.7–18.6%) and for Europe 16.2% (12.6–19.7%). Anaemia in pregnancy is associated with increased risk of adverse outcomes for the mother and baby. Iron (and folic acid) supplements during pregnancy in women at risk of IDA are an important recommendation by the WHO.2 However, it is unclear if women should receive targeted supplementation (after screening … [1]: {openurl}?query=rft.jtitle%253DAnn%2BIntern%2BMed%26rft.volume%253D162%26rft.spage%253D566%26rft_id%253Dinfo%253Adoi%252F10.7326%252FM14-2932%26rft_id%253Dinfo%253Apmid%252F25820661%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.7326/M14-2932&link_type=DOI [3]: /lookup/external-ref?access_num=25820661&link_type=MED&atom=%2Febmed%2F20%2F6%2F208.atom

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.083
GPT teacher head0.361
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2015
Admission routes1
Has abstractyes

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